TY - JOUR
T1 - Initialized Earth System prediction from subseasonal to decadal timescales
AU - Meehl, Gerald A.
AU - Richter, Jadwiga H.
AU - Teng, Haiyan
AU - Capotondi, Antonietta
AU - Cobb, Kim
AU - Doblas-Reyes, Francisco
AU - Donat, Markus G.
AU - England, Matthew H.
AU - Fyfe, John C.
AU - Han, Weiqing
AU - Kim, Hyemi
AU - Kirtman, Ben P.
AU - Kushnir, Yochanan
AU - Lovenduski, Nicole S.
AU - Mann, Michael E.
AU - Merryfield, William J.
AU - Nieves, Veronica
AU - Pegion, Kathy
AU - Rosenbloom, Nan
AU - Sanchez, Sara C.
AU - Scaife, Adam A.
AU - Smith, Doug
AU - Subramanian, Aneesh C.
AU - Sun, Lantao
AU - Thompson, Diane
AU - Ummenhofer, Caroline C.
AU - Xie, Shang Ping
N1 - Publisher Copyright:
© 2021, Springer Nature Limited.
PY - 2021/5
Y1 - 2021/5
N2 - Initialized Earth System predictions are made by starting a numerical prediction model in a state as consistent as possible to observations and running it forward in time for up to 10 years. Skilful predictions at time slices from subseasonal to seasonal (S2S), seasonal to interannual (S2I) and seasonal to decadal (S2D) offer information useful for various stakeholders, ranging from agriculture to water resource management to human and infrastructure safety. In this Review, we examine the processes influencing predictability, and discuss estimates of skill across S2S, S2I and S2D timescales. There are encouraging signs that skilful predictions can be made: on S2S timescales, there has been some skill in predicting the Madden–Julian Oscillation and North Atlantic Oscillation; on S2I, in predicting the El Niño–Southern Oscillation; and on S2D, in predicting ocean and atmosphere variability in the North Atlantic region. However, challenges remain, and future work must prioritize reducing model error, more effectively communicating forecasts to users, and increasing process and mechanistic understanding that could enhance predictive skill and, in turn, confidence. As numerical models progress towards Earth System models, initialized predictions are expanding to include prediction of sea ice, air pollution, and terrestrial and ocean biochemistry that can bring clear benefit to society and various stakeholders.
AB - Initialized Earth System predictions are made by starting a numerical prediction model in a state as consistent as possible to observations and running it forward in time for up to 10 years. Skilful predictions at time slices from subseasonal to seasonal (S2S), seasonal to interannual (S2I) and seasonal to decadal (S2D) offer information useful for various stakeholders, ranging from agriculture to water resource management to human and infrastructure safety. In this Review, we examine the processes influencing predictability, and discuss estimates of skill across S2S, S2I and S2D timescales. There are encouraging signs that skilful predictions can be made: on S2S timescales, there has been some skill in predicting the Madden–Julian Oscillation and North Atlantic Oscillation; on S2I, in predicting the El Niño–Southern Oscillation; and on S2D, in predicting ocean and atmosphere variability in the North Atlantic region. However, challenges remain, and future work must prioritize reducing model error, more effectively communicating forecasts to users, and increasing process and mechanistic understanding that could enhance predictive skill and, in turn, confidence. As numerical models progress towards Earth System models, initialized predictions are expanding to include prediction of sea ice, air pollution, and terrestrial and ocean biochemistry that can bring clear benefit to society and various stakeholders.
UR - http://www.scopus.com/inward/record.url?scp=85108369859&partnerID=8YFLogxK
U2 - 10.1038/s43017-021-00155-x
DO - 10.1038/s43017-021-00155-x
M3 - Review article
AN - SCOPUS:85108369859
SN - 2662-138X
VL - 2
SP - 340
EP - 357
JO - Nature Reviews Earth and Environment
JF - Nature Reviews Earth and Environment
IS - 5
ER -